Deploying Roadside Unit Efficiently in VANETs: A Multi-Objective Delay-Based Optimization Strategy Using Lagrangian Relaxation
Bingjie Liang, Wenqi Lu, Bin Ran
Abstract
Vehicular Ad hoc Networks (VANETs) in intelligent transportation systems have been regarded as an effective means to alleviate traffic congestion, reduce traffic accidents and save fuel. A proper roadside unit (RSU) deployment strategy is essential to improve the efficiency and stability of VANETs’ communication. However, the RSU deployment strategy that combines coverage and quality of service is still limited. To provide city planners with decision-making support, a multi-objective optimization model is built to optimize the deployment of RSUs under a limited budget. Two objective functions are proposed to maximize the number of communication tasks served and minimize the total task-weighted delay. Through a simple transformation of the delay matrix, we transform the proposed multi-objective model into a p-median problem. Then, we design a Lagrangian relaxation algorithm in a multi-objective framework to solve the model. Moreover, simulation examples are presented to demonstrate and validate the proposed model and solution algorithm. We analyze the gap between the algorithm result and the optimal solution, and characterize the Pareto front. The simulation results verify the feasibility and effectiveness of the proposed model and algorithm.